【目的/意義】系統性分析知識擴散相關的模型和過程。【方法/過程】本文通過對知識分享型網絡平臺-"知乎"網絡上知識擴散的實例數據抓取和分析,提出了能夠更加真實反映知識擴散的網絡演化模型和擴散模型。進而,通過計算機仿真,分析了知識擴散模型中相關參數對知識擴散過程和結果的影響。【結果/結論】通過知識擴散實例的數據抓取和分析,確定了以BBV加權網絡演化模型和Bass擴散模型為主的知識擴散模型。通過參數分析,確定了BBV加權網絡中網絡權重和Bass模型中外部影響因子能夠顯著加速知識擴散。在實際應用中,如果忽略了這些因素,對于知識擴散的過程和結果都難以得到正確的預測。

【Purpose/significance】This paper addresses the modeling and the process of knowledge dissemination.【Method/process】Through data collecting from one of most popular online knowledge-sharing social media, ZHIHU, a weighted network generation algorithm and a knowledge dissemination model are proposed to represent dynamic process of knowledge dissemination. Based on these models, the methodology of computer simulation is introduced to analyze the process of knowledge dissemination, and influence of parameters of the models.【Result/conclusion】According to the real data from the ZHIHU, the BBV weighted network evolution model and the Bass model are verified to represent the dissemination of knowledge. More important, the link weight of BBV network and the external factor of Bass model have significant influence on the process of knowledge dissemination. If these parameters are ignored or omitted, it will be difficult to forecast the process and results of knowledge dissemination.